Experiments from NER task in Spanish language using CoNLL-2002 and Mexican news datasets

🦠 A framework that leverages machine translation and the BERT model for performing multi-lingual sentiment polarity detection of COVID-19 tweets posted in Hindi language on Twitter.

Data Science Project (Australian Electricity Load Dataset Analysis)

Apply RNN for sentiment analysis.

Dependency parsing was used to extract relevant information from a review in order to predict the sentiment of a given aspect term. Different machine learning models such as Naïve Bayes, Logistic Regression, Support Vector Classifier and Neural Networks were used to make predictions. A maximum accuracy score of 0.74 on the test dataset was achie…

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Disaster information extraction using named entity recognition, we have incorporated a machine learning model which predicts entites in a given iput.

Trained over 60,000 IMDB rating to categorize positive and negative review

A deep learning project for classifying news articles as real or fake using a Bidirectional LSTM model. It includes steps for preprocessing text data, building and training the model, and evaluating its performance.

This repo contains the code for summarizing financial reports with increased factual correctness for quantitative researchers.

Trained over 2,000 BBC News to categorize unseen articles into 5 categories namely Sport, Tech, Business, Entertainment and Politics.